code: def __init__(self):
      super(AlexNet_Bottom, self).__init__()
      self.features = []
      self.layer0 = nn.Sequential(
          ConvBlock(3, 64, kernel_size=5, stride=1, padding=2),
          nn.BatchNorm2d(64),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(kernel_size=2, stride=2),
      )
      self.layer1 = nn.Sequential(
          ConvBlock(64, 192, kernel_size=5, stride=1, padding=2),
          nn.BatchNorm2d(192),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(kernel_size=2, stride=2),
      )
      for i in range(2):
          layer = getattr(self, f"layer{i}")
          self.features.append(layer)
  
imports: from torch.nn import init
  import sys
  import torch
  import torch
  import torchvision
  from torch import nn
  from datetime import datetime
  from fate.ml.nn.homo.fedavg import FedAVGClient, TrainingArguments
  from fate.ml.nn.model_zoo.agg_layer.fedpass._passport_block import ConvPassportBlock
  from fate.ml.nn.model_zoo.agg_layer.fedpass.agg_layer import FedPassAggLayerHost, FedPassAggLayerGuest
  from tqdm import tqdm
  from fate.ml.nn.model_zoo.hetero_nn_model import HeteroNNModelGuest, HeteroNNModelHost
  from fate.ml.nn.hetero.hetero_nn import HeteroNNTrainerGuest, HeteroNNTrainerHost, TrainingArguments
label_desc: Use image node_id 1 to create a new AlexNet_Bottom object from inherited base classes: nn with example: obj = AlexNet_Bottom()